Integrating Event-Based and Biophysical Models to Predict Individual Tau Progression in Alzheimer's Disease Article Swipe
Robin Sandell
,
Justin Torok
,
Srikantan S. Nagarajan
,
Kamalini G. Ranasinghe
,
Daren Ma
,
Ashish Raj
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1109/isbi60581.2025.10981024
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1109/isbi60581.2025.10981024
Alzheimer's Disease (AD) is characterized by the accumulation of tau neurofibrillary tangles, which spread along the brain's white matter tracts and correlate with cognitive de-cline. Modeling and predicting tau progression is crucial for developing of therapeutic treatments, but current approaches provide limited insight into individual variation. This study combines statistical and biophysical modeling approaches to capture individuals' longitudinal tau spread. We employed an event-based model (EBM) to identify time-evolving pathology patterns in 650 Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects. We then fit a biophysical network diffusion model (NDM) to the resulting tau trajectories. By optimizing the initial tau pattern of the NDM, we achieved a strong fit to individuals' empirical data, enabling predictions of past and future tau. Our findings reveal a phenomenon of convergence of inter-region and inter-subject tau over time, as well as two underlying seed archetypes. Our novel integration of event-based and biophysical modeling may prove clinically valuable and further an understanding of heterogeneity in AD pathophysiology.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/isbi60581.2025.10981024
- OA Status
- gold
- References
- 7
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- 10
- OpenAlex ID
- https://openalex.org/W4410297612
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4410297612Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/isbi60581.2025.10981024Digital Object Identifier
- Title
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Integrating Event-Based and Biophysical Models to Predict Individual Tau Progression in Alzheimer's DiseaseWork title
- Type
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
- Publication date
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2025-04-14Full publication date if available
- Authors
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Robin Sandell, Justin Torok, Srikantan S. Nagarajan, Kamalini G. Ranasinghe, Daren Ma, Ashish RajList of authors in order
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https://doi.org/10.1109/isbi60581.2025.10981024Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
- OA URL
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https://escholarship.org/uc/item/4w2936mdDirect OA link when available
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Computer science, Disease, Event (particle physics), Neuroscience, Psychology, Medicine, Physics, Pathology, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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7Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.phenomenon | 122 |
| abstract_inverted_index.predicting | 27 |
| abstract_inverted_index.underlying | 136 |
| abstract_inverted_index.variation. | 45 |
| abstract_inverted_index.Alzheimer's | 0, 73 |
| abstract_inverted_index.archetypes. | 138 |
| abstract_inverted_index.biophysical | 51, 83, 145 |
| abstract_inverted_index.convergence | 124 |
| abstract_inverted_index.event-based | 63, 143 |
| abstract_inverted_index.integration | 141 |
| abstract_inverted_index.predictions | 112 |
| abstract_inverted_index.progression | 29 |
| abstract_inverted_index.statistical | 49 |
| abstract_inverted_index.therapeutic | 35 |
| abstract_inverted_index.treatments, | 36 |
| abstract_inverted_index.Neuroimaging | 75 |
| abstract_inverted_index.accumulation | 7 |
| abstract_inverted_index.individuals' | 56, 108 |
| abstract_inverted_index.inter-region | 126 |
| abstract_inverted_index.longitudinal | 57 |
| abstract_inverted_index.characterized | 4 |
| abstract_inverted_index.heterogeneity | 156 |
| abstract_inverted_index.inter-subject | 128 |
| abstract_inverted_index.time-evolving | 68 |
| abstract_inverted_index.trajectories. | 92 |
| abstract_inverted_index.understanding | 154 |
| abstract_inverted_index.neurofibrillary | 10 |
| abstract_inverted_index.pathophysiology. | 159 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.21490521 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |